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Now showing items 11-12 of 12
Design and Development of Naive Bayes Classifier
(North Dakota State University, 2013)
The naïve Bayes classifier is a simple form of Bayesian classifiers which assumes all the features are independent of each other. Despite this assumption, the naïve Bayes classifier’s accuracy is comparable to other ...
Object Classification Using Stacked Autoencoder and Convolutional Neural Network
(North Dakota State University, 2016)
In the recent years, deep learning has shown to have a formidable impact on object classification and has bolstered the advances in machine learning research. Many image datasets such as MNIST, CIFAR-10, SVHN, Imagenet, ...